The CD6/ALCAM pathway promotes lupus nephritis via T cell–mediated responses

T cells are central to the pathogenesis of lupus nephritis (LN), a common complication of systemic lupus erythematosus (SLE). CD6 and its ligand, activated leukocyte cell adhesion molecule (ALCAM), are involved in T cell activation and trafficking. Previously, we showed that soluble ALCAM is increased in urine (uALCAM) of patients with LN, suggesting that this pathway contributes to disease. To investigate, uALCAM was examined in 1038 patients with SLE and LN from 5 ethnically diverse cohorts; CD6 and ALCAM expression was assessed in LN kidney cells; and disease contribution was tested via antibody blockade of CD6 in murine models of SLE and acute glomerulonephritis. Extended cohort analysis offered resounding validation of uALCAM as a biomarker that distinguishes active renal involvement in SLE, irrespective of ethnicity. ALCAM was expressed by renal structural cells whereas CD6 expression was exclusive to T cells, with elevated numbers of CD6+ and ALCAM+ cells in patients with LN. CD6 blockade in models of spontaneous lupus and immune-complex glomerulonephritis revealed significant decreases in immune cells, inflammatory markers, and disease measures. Our data demonstrate the contribution of the CD6/ALCAM pathway to LN and SLE, supporting its use as a disease biomarker and therapeutic target.

ALCAM levels were normalized by urine creatinine levels. Urine creatinine levels were measured by the Creatinine Parameter Assay Kit (KGE005, R&D Systems, Minneapolis, MN).

Quantitation of TNF-α and IFN− in urine
Urine samples from the cohort derived at UT Southwestern Medical Center described previously ((32), Supplementary Table S1). 23 human subjects (7 active LN, 8 inactive SLE, 8 healthy controls, all female, age range 23-42 years) were interrogated for the levels of 1129 distinct human proteins using a pre-fabricated aptamer-based-targeted proteomic assay (32). The interrogated proteins included ALCAM, IFN-γ, and TNF-α. Obtained values were normalized to urine creatinine.

Quantitation of CD318 in serum and urine
Matched urine and serum samples from LN, inactive SLE, and active non-renal patients were obtained from the Albert Einstein College of Medicine. Informed consent was obtained for each patient for the urine and serum collections, and the study was approved by the institutional review board at Albert Einstein College of Medicine. Clinical data were obtained with each sample collection. For the LN group, samples were obtained within 2 weeks of a renal biopsy sample showing active LN. Inactive disease was defined as SLEDAI <=2, while active non-renal disease was defined as a SLEDAI >=6 and a rSLEDAI=0. Patient characteristics are summarized in Supplementary Table S3. Urine and serum CD318 levels were measured using the Human CDCP1 DuoSet ELISA (R&D Systems, Minneapolis, MN). Assay was performed according to the manufacturer's instructions. Serum was diluted 1:100 and urine was diluted 1:20 in assay buffer. These dilutions were determined from pilot experiments examining the optimal dilution to prevent inhibition of detection due to the matrix (i.e. serum, urine). Concentration of soluble CD318 in serum and urine samples were interpolated from a standard curve using a four-parameter logistic (4PL) curve fit. Molar concentration for ALCAM-Fc and CD318-Fc was used to ensure that plates were coated with the equivalent number of molecules. After incubation, the plates were washed once with PBS, and then blocked for 30 min with 1% BSA at 37 o C followed by two additional washes with PBS.

RNASeq data analysis
Data from single-cell RNA sequencing (scRNA-seq) profiles of clinically indicated renal biopsies obtained from patients with active LN were acquired through the Accelerated Medicines Partnership (AMP) (35). Patient characteristics are contained in Supplementary Table S4. All the scRNA-seq data were analyzed collectively. Cell type identification and clustering was performed with principal component analysis and t-Distributed Stochastic Neighbor Embedding (tSNE) using the Seurat package (version 2.2.1) for R. Briefly, the count matrices were depth-normalized to 10,000 reads and used to identify the set of genes that was most variable across datasets.
Ubiquitously expressed genes, such as mitochondrially encoded proteins, were excluded for clustering and removed after variable genes were identified. After clusters were established with tSNE, cell types were identified by examination of expression profiles within each cluster (62).  Supplementary Figure 3. Comparison of T cell co-stimulation by ALCAM and CD318. PBMCs were left unstimulated or stimulated using plate-bound anti-CD3 alone, anti-CD3 + recombinant ALCAM-Fc, or anti-CD3+ recombinant CD318-Fc. After 24 hours, cells were collected and analyzed by flow cytometry. T cells were identified using CD3, CD4, CD8, CD45RA, and CCR7. Graphs depict cell surface expression, represented as geometric mean fluorescent intensity (gMFI), of activation markers CD25, CD40L, CD71, PD-1, and TIM3 on CD4 T cells. Data represent mean ± SE. Comparisons between groups were evaluated using one-way ANOVA with multiple-comparisons test. ***p<0.0001; ** p<0.001; ** p<0.01; * p<0.05.